ESTRO 2020 Abstract book

S957 ESTRO 2020

and patients’ positions. Deformable image registration is a novel process to align target images to reference images. This process allows the internal deformation of pixel-to- pixel co-ordination of target images. Theoretically, this technology can generate new deformed CT images (DCT) from initial planning CT images. Our research question is to answer whether we can use DCT instead of re-planning CT images for treatment planning. In our hypothesis, the gamma passing rate of 3%/3mm criteria between each comparison is expected to be equal or more than 95%. Material and Methods Five patients with nasopharyngeal cancer treated with volumetric arc therapy were enrolled. Computed tomography images (CT1) were obtained for initial radiation planning. The final plan with beams parameter and configuration (Beams P) were achieved for actual treatment with dose delivered on the first fraction. During the radiation therapy course, re-planning CT images (CT2) were performed during the 4th week of treatment. Beams P were re-calculated on CT2 and named as Hybrid plan with dose delivered as DOSE-HYBRID . Extended cone-beam CT (CBCT) scans were performed in specific fractions and extended CBCT images during the 4th week of treatment called CBCT2. Velocity software (Varian medical system) version 3.2.0 was used for deformation processes. Deformed CT images-3 (DCT3) were constructed by using CT1 to CBCT2 deformable image registration. Beams P were re- calculated on DCT3 with calculated dose as DOSE-DCT3 . Dose distribution on DOSE-HYBRID and DOSE-DCT3 were compared by using gamma criteria 3%/3mm. The pass rates were recorded using both 3D and 2D gamma analyses. 2D gamma analyses were done on each image from 100 mm above to 100 mm below treatment isocenters. In addition, dose distribution on organs of interest on each plan was compared. Results Average pass rate using 3D gamma analysis of 3%/3mm criteria (with below 10% max dose suppression) between DOSE-HYBRID and DOSE-DCT3 is 93.84%. After excluding data from the shoulder region on 2D gamma analyses, an average 2D gamma pass rate using the same criteria is rising to 98.12%. D2% of the spinal cord, brainstem, GTVp, GTVn on each plan are within 5% deviation of the initial plans. However, doses D2% of the optic chiasm are extremely deviated (-50.8% to 102.3%).

Conclusion In this study, the average pass rate using 3D gamma criteria 3%/3mm between DOSE-HYBRID and DOSE-DCT3 is not meet our expectations. However, this result is comparable with the mean pass rate of composite fields in head and neck cases from AAPM TG 119. Despite several limitations, there are interesting results from 2D analysis and D2% DVH comparison. Further study is essentially requisite before using in any clinical implications. PO-1650 Evaluating plan robustness for organ deformation and set-up uncertainties in head and neck cancer J. Robbins 1 , M. Van Herk 1 , A. Green 1 , B. Eiben 2 , A. McPartlin 3 , E. Vásquez Osorio 1 1 University of Manchester, Division of Cancer Sciences, Manchester, United Kingdom ; 2 University College London, Centre for Medical Image Computing- Department of Medical Physics and Biomedical Engineering, London, United Kingdom ; 3 The Christie NHS Foundation Trust, Clinical Oncology, Manchester, United Kingdom Purpose or Objective In radiotherapy, a planning CT (pCT) is used to plan treatment, however the pCT only shows a snapshot of the patient anatomy at a particular point in time. As the treatment is delivered in multiple fractions several days after the pCT is acquired, it is expected that the patient’s internal anatomy will change throughout the treatment course as organs may deform. Additionally, patient positioning on the couch may vary for each fraction, e.g. due to set-up uncertainty. These two factors cause uncertainties in the dose absorbed by the patient. In this study we model these uncertainties and simulate the joint effect they have on treatments. Material and Methods Data from 20 patients were used. Organ deformations were modelled using 6 independent weekly principal component analysis (PCA) models based on the pCT and 6 weekly cone- beam CT scans from 13 patients. To account for time trends in organ deformations, 5 daily vector fields were simulated from each of the 6 weekly PCA models. Systematic and random set-up uncertainties were modelled as Gaussian distributions with standard deviations of ∑ = 0, 1, 2 mm and σ = 1, 2 mm respectively. We simulated 100 30-fraction treatments using the clinical plan for each patient, accounting for: 1) only organ deformations, 2) only set-up errors, and 3) both organ deformations and set-up errors. The difference in the maximum brainstem dose and mean dose to each parotid from the planned dose to the simulated doses was evaluated for the training and validation (n = 7) datasets separately. Results Figure 1 shows the difference in the resulting DVH parameters from the planning value for all simulated